We focus on the task of extracting multiple tuples with overlapping entities from sentences. We choose the New York Times (NYT) corpus for our experiments. This corpus has multiple versions, and we choose the following two versions as their test dataset has a significantly larger number of instances of multiple relation tuples with overlapping entities. (i) The first version is used by [1]} (mentioned as NYT in their paper) and has 24 relations. We name this version as NYT24. This dataset is derived from the NYT11 dataset of the previous chapter. The test data of NYT11 do not have any sentences with multiple tuples or overlapping tuples. But the training data of NYT11 have such sentences. So they split the training data of NYT11 to create the test data for the joint extraction task. (ii) The second version is used by [2]} (mentioned as NYT10 in their paper) and has 29 relations. We name this version as NYT29. This dataset is derived from the NYT10 dataset of the previous chapter. They remove those relations from the dataset which do not appear in the test dataset. We select 10% of the original training data and use it as the validation dataset. The remaining 90% is used for training. We include statistics of the training and test datasets in Table REF . Both NYT24 and NYT29 datasets do not contain any sentence with zero positive tuples.
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